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| from typing import Dict, Any | |
| class ClinicalAssessmentEngine: | |
| """ | |
| Ithu thaan namba main Local AI Engine. Neenga kudutha ella list-aiyum | |
| (Depression types, Alleviation states, Attrition reasons, Patient Intent) | |
| ithulla exact-a train panna porom. | |
| """ | |
| def __init__(self): | |
| # Placeholder for loading actual BERT / LLM pipeline | |
| # e.g., self.model = pipeline('text-classification', model='medical-bert') | |
| # --- THE MASTER CLINICAL TAXONOMY (As strictly defined by you) --- | |
| self.master_categories = { | |
| "Main_Clinical_Types": [ | |
| "Major Depressive Disorder (MDD)", "Persistent Depressive Disorder (PDD / Dysthymia)", | |
| "Bipolar Disorder (Manic Depression)", "Postpartum (Perinatal) Depression", | |
| "Seasonal Affective Disorder (SAD)", "Psychotic Depression", | |
| "Premenstrual Dysphoric Disorder (PMDD)", "Atypical Depression" | |
| ], | |
| "Clinical_Sub_Types": [ | |
| "Disruptive Mood Dysregulation Disorder (DMDD)", "Treatment-Resistant Depression (TRD)", | |
| "Substance/Medication-Induced Depression", "Depression Due to Another Medical Condition", | |
| "Smiling Depression (High-Functioning)", "Melancholic Depression", | |
| "Agitated Depression", "Double Depression", "Minor Depression" | |
| ], | |
| "Rare_and_Specific_Origins": [ | |
| "Catatonic Depression", "Endogenous Depression", "Reactive (Exogenous) Depression", | |
| "Existential Depression", "Masked Depression", "Geriatric Depression", | |
| "Recurrent Brief Depression", "Unipolar Depression", "Vascular Depression" | |
| ], | |
| "Niche_Types": [ | |
| "Cyclothymia", "Mixed Anxiety-Depressive Disorder", "Perimenopausal Depression", | |
| "Post-Schizophrenic Depression", "Adjustment Disorder", "Antenatal (Prenatal) Depression", | |
| "Prolonged Grief Disorder", "Male Depressive Syndrome", "Burnout-Induced Depression", | |
| "Anergic Depression", "D-MER (Dysphoric Milk Ejection Reflex)", "Post-coital Dysphoria (PCD)" | |
| ], | |
| "Treatment_Alleviation_States": [ | |
| "Partial Response", "Residual Symptoms", "Tachyphylaxis (Poop-Out)", | |
| "Breakthrough Depression", "Treatment-Resistant (TRD)", "Full Remission", | |
| "Sustained Recovery", "Spontaneous Remission", "Placebo Effect", | |
| "Palliative Alleviation", "Nocebo Effect", "The Honeymoon Effect", | |
| "Relapse", "Recurrence", "Pseudo-Resistance", "Emotional Blunting (Apathy)", | |
| "Treatment-Emergent Affective Switch (TEAS)", "Discontinuation Syndrome (Withdrawal)" | |
| ], | |
| "Attrition_and_Loss_Of_FollowUp": [ | |
| # Attrition Domains | |
| "Corporate/HR Attrition", "Customer Churn", "Academic Attrition (Dropouts)", | |
| "Therapeutic/Clinical Trial Attrition", | |
| # Patient Intent Loss | |
| "Voluntary Withdrawal", "Intentional Non-compliance", "Cured Perception", "Unintentional Loss", | |
| # Reachability | |
| "Silent Loss", "Passive Dropout", "Active Dropout", | |
| # Clinical Outcomes | |
| "Mortality (Death)", "Severe Morbidity", | |
| # Barriers | |
| "Geographic Attrition", "Economic Attrition", "Social Stigma", | |
| # System Failures | |
| "Administrative Loss", "Provider Relocation", "Protocol Burden", | |
| # Timelines | |
| "Intermittent Loss", "Permanent Loss" | |
| ] | |
| } | |
| def evaluate_patient_state(self, patient_text: str) -> Dict[str, Any]: | |
| """ | |
| Patient chat pannumbothu intha function than antha Text-a read panni, | |
| mela irukkura antha categories-la etha match aaguthu nu theliva analyze pannum. | |
| """ | |
| # ========================================== | |
| # REAL AI LOGIC WILL BE IMPLEMENTED HERE | |
| # (Tokenizing, running through BERT, extracting exact category) | |
| # ========================================== | |
| # MOCK RETURN FOR NOW based on rule definitions | |
| return { | |
| "mapped_condition": "Smiling Depression (High-Functioning)", | |
| "mapped_treatment_state": "Incomplete Relief", | |
| "attrition_risk": "High (Possible Passive Dropout)", | |
| "requires_doctor": False, | |
| "extracted_feeling": "Hiding deep sadness while working normally." | |
| } | |
| # Initialize a global instance to be used by the FastAPI router | |
| analyzer_engine = ClinicalAssessmentEngine() | |